of organizations seeking to scale digital business are likely to fail because they do not take a modern approach to data governance.
of organizations believe a lack of data governance is the main data challenge inhibiting AI initiatives.
of CIOs and technology leaders identify data governance as their second-highest challenge for the next three to five years.
of IT Leaders Identify Data Quality as a Major Barrier to AI Success.
higher analytics ROI is achieved by organizations with mature data governance driven by stronger data quality.
of enterprises are creating "data products," which are consumable data assets that solve specific business problems.
reduction in compliance costs is likely to be achieved through robust data governance frameworks that streamline controls, improve audit readiness, and minimize regulatory risk.
of companies have increased their spending on data governance solutions to ensure data is secure, accurate, and usable.
Unified Data Catalog & Discovery Bring all data assets, domains, and metadata together for instant search and lineage visibility.
Business Glossary & Data Domains Define common terms, owners, and rules to ensure consistent under standing across the en terprise.
Products, Assets & Stewardship Hub Manage data as a governed product with clear ownership, quality, and usage visibility.
Intelligent Policy & Access Governance Automate policies and fine-grained access to keep data secure, compliant, and trusted.
of CDAOs will prioritise governance-driven data quality as the foundation of AI and analytics success.
reduction in data-preparation overhead and 3× faster time-to-insight will be achieved by organization with mature data catalogs.
respondents anticipate to see a major impact from AI capabilities on their team’s data management efficiency.
of enterprises will adopt domain-based, federated governance models to manage distributed data estates.